This edited volume contains 16 research articles. It presents recent and pressing issues in stochastic processes, control theory, differential games, optimization, and their applications in finance, manufacturing, queueing networks, and climate control. One of the salient features is that the...

This paper presents an asymptotic analysis of hier­archical marketing-production systems with stochastic demand and stochastic production capacity (machines are subject to bre­akdown and repair). Our control variables are advertising and production rates which influence demand and inventory...

We develop a general methodology for a partially observed stochastic control problem. The dynamics is governed by a discrete-time Markov process. We describe an application to an inventory system with possibility of shrinkage, and introduce unnormalized conditional probabilities to transform the...

In this paper, the problem of machine replacement in a changing technological environment is formulated as a problem in modern control theory. The objective is to maximize the present value of all future net profits over a class of infinite chains of machines where each link in the chain...

Linear optimal control problems with state inequality constraints is an important class of large systems. This paper shows that a generalized programming formulation of these problems does not result in a decomposition over time or a maximum principle as it does for problems without the state...

In this paper, we identify a new class of stochastic Iinear convex optimal control problems, whose solution can be obtained by solving appropriate equivalent deterministic optimal control problems. The term 'linear convex' is meant to imply that the dynamics is linear and the cost function is...

This paper derives a maximum principle for dynamic systems with continuous lags, i.e., systems governed by integrodifferential equations, using dynamic programming. As a result, the adjoint variables can be provided with useful economic interpretations

We consider a finite-horizon control model with additive input. There are two convex functions which describe the running cost and the terminal cost within the system. The cost of input is proportional to the input and can take both positive and negative values. It is shown that there exists a...